Development of smart grid techniques is globally taking place mainly for the purpose of adaptation of energy distribution infrastructures to low-carbon society, reinforcement of stable supply and enhancement of economy. One of diverse smart grid techniques is demand side management in which demanders are requested to change the operating state of installed equipment, thus realizing relaxation of load concentration in the electric power system and utilization of surplus electricity based on dispersed power sources.
For example, Patent Literature 1 describes a demand side management technique. In this technique, if there is a time slot when load concentration is anticipated in the future such as the following day in an electric power supply system, demanders are requested to reduce energy consumption. Then, demanders that shift energy utilization to another time slot in response to the request are given an incentive such as being able to receive a discount on electricity rates as a reward. Consequently, reduction or dispersion of the load concentration state in the electric power supply system can be expected.
In demand side management, it is important to predict the size of demand in advance in order to properly decide the amount of reduction (in some case, the amount of increase) in energy consumption. Demand prediction is also important in order to properly define an energy supply plan.
Patent Literature 2 discloses that, based on a control signal that commands a demander's load equipment (for example, an air conditioning machine) to adjust load, a server for demand side management generates and stores operation result data of the load equipment (for example, start time and stop time, duration of operation, load factor, whether there is a load adjustment or not, result of load adjustment (for example, limiting the upper load limit to 70% of rated load) or the like), and carries out demand prediction for future and decision of a load adjustment range based on the past load operation result data.
Techniques for demand prediction are also disclosed in Patent Literatures 3, 4 and the like.